Search results for: customer service performance (B2B)

Authors: Samah Jawad Jabari

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Water is the most important and valuable resource not only for human life but also for all living things on the planet. The water supply utilities should fulfill the water requirement quantitatively and qualitatively. Drinking water systems are exposed to both natural (hurricanes and flood) and manmade hazards (risks) that are common in Palestine. Non-Revenue Water (NRW) is a manmade risk which remains a major concern in Palestine, as the NRW levels are estimated to be at a high level. In this research, Hebron city water distribution network was taken as a case study to estimate and audit the NRW levels. The research also investigated the state of the existing water distribution system in the study area by investigating the water losses and obtained more information on NRW prevention and management practices. Data and information have been collected from the Palestinian Water Authority (PWA) and Hebron Municipality (HM) archive. In addition to that, a questionnaire has been designed and administered by the researcher in order to collect the necessary data for water auditing. The questionnaire also assessed the views of stakeholder in PWA and HM (staff) on the current status of the NRW in the Hebron water distribution system. The important result obtained by this research shows that NRW in Hebron city was high and in excess of 30%. The main factors that contribute to NRW were the inaccuracies in billing volumes, unauthorized consumption, and the method of estimating consumptions through faulty meters. Policy for NRW reduction is available in Palestine; however, it is clear that the number of qualified staff available to carry out the activities related to leak detection is low, and that there is a lack of appropriate technologies to reduce water losses and undertake sufficient system maintenance, which needs to be improved to enhance the performance of the network and decrease the level of NRW losses.

Keywords: non-revenue water, water auditing, leak detection, water meters

Procedia PDF Downloads 300

Authors: Harini Chakkera

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Background: Inpatient hyperglycemia is an established independent risk factor among several patient cohorts with hospital readmission. This has not been studied after kidney transplantation. Nearly one-third of patients who have undergone a kidney transplant reportedly experience 30-day readmission. Methods: Data on first-time solitary kidney transplantations were retrieved between September 2015 to December 2018. Information was linked to the electronic health record to determine a diagnosis of diabetes mellitus and extract glucometeric and insulin therapy data. Univariate logistic regression analysis and the XGBoost algorithm were used to predict 30-day readmission. We report the average performance of the models on the testing set on five bootstrapped partitions of the data to ensure statistical significance. Results: The cohort included 1036 patients who received kidney transplantation, and 224 (22%) experienced 30-day readmission. The machine learning algorithm was able to predict 30-day readmission with an average AUC of 77.3% (95% CI 75.30-79.3%). We observed statistically significant differences in the presence of pretransplant diabetes, inpatient-hyperglycemia, inpatient-hypoglycemia, and minimum and maximum glucose values among those with higher 30-day readmission rates. The XGBoost model identified the index admission length of stay, presence of hyper- and hypoglycemia and recipient and donor BMI values as the most predictive risk factors of 30-day readmission. Additionally, significant variations in the therapeutic management of blood glucose by providers were observed. Conclusions: Suboptimal glucose metrics during hospitalization after kidney transplantation is associated with an increased risk for 30-day hospital readmission. Optimizing the hospital blood glucose management, a modifiable factor, after kidney transplantation may reduce the risk of 30-day readmission.

Keywords: kidney, transplant, diabetes, insulin

Procedia PDF Downloads 92

Authors: Teja Sai Puligadda

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Satellite images in detail can serve an important role in the geographic study. Quantitative and qualitative information provided by the satellite and remote sensing images minimizes the complexity of work and time. Data/images are captured at regular intervals by satellite remote sensing systems, and the amount of data collected is often enormous, and it expands rapidly as technology develops. Interpreting remote sensing images, geographic data mining, and researching distinct vegetation types such as agricultural and forests are all part of satellite image categorization. One of the biggest challenge data scientists faces while classifying satellite images is finding the best suitable classification algorithms based on the available that could able to classify images with utmost accuracy. In order to categorize satellite images, which is difficult due to the sheer volume of data, many academics are turning to deep learning machine algorithms. As, the CNN algorithm gives high accuracy in image recognition problems and automatically detects the important features without any human supervision and the ANN algorithm stores information on the entire network (Abhishek Gupta., 2020), these two deep learning algorithms have been used for satellite image classification. This project focuses on remote sensing through Deep Neural Networks i.e., ANN and CNN with Deep Sat (SAT-4) Airborne dataset for classifying images. Thus, in this project of classifying satellite images, the algorithms ANN and CNN are implemented, evaluated & compared and the performance is analyzed through evaluation metrics such as Accuracy and Loss. Additionally, the Neural Network algorithm which gives the lowest bias and lowest variance in solving multi-class satellite image classification is analyzed.

Keywords: artificial neural network, convolutional neural network, remote sensing, accuracy, loss

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Authors: Kusay Wheib, Alexandra Krvchenko

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Crop yields are influenced by many factors, including natural ones, such as soil and environmental characteristics of the agricultural land, as well as manmade ones, such as management applications. One of the factors that frequently affect crop yields in undulating Midwest landscapes is topography, which controls the movement of water and nutrients necessary for plant life. The main objective of this study is to examine how field topography influences performance of different management practices in undulated terrain of southwest Michigan. A total of 26 agricultural fields, ranging in size from 1.1 to 7.4 ha, from the Scale-Up at Kellogg Biological Station were included in the study. The two studied factors were crop species with three levels, i.e., corn (Zea mays L.) soybean (Glycine max L.), and wheat (Triticum aestivum L.), and management practice with three levels, i.e., conventional, low input, and organic managements. They were compared under three contrasting topographical settings, namely, summit (includes summits and shoulders), slope (includes backslopes), and depression (includes footslope and toeslope). Yield data of years 2007 through 2012 was processed, cleaned, and filtered, average yield then was calculated for each field, topographic setting, and year. Topography parameters, including terrain, slope, curvature, flow direction and wetness index were computed under ArcGIS environment for each topographic class of each field to seek their effects on yield. Results showed that topographical depressions produced greatest yields in most studied fields, while managements with chemical inputs, both low input and conventional, resulted in higher yields than the organic management.

Keywords: sustainable agriculture, precision agriculture, topography, yield

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Authors: R. Kerbachi, S. Chikhi, M. Boughedaoui

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The study presents an analysis of the Algerian vehicle fleet and resultant emissions. The emission measurement of air pollutants emitted by road transportation (CO, THC, NOX and CO2) was conducted on 17 light duty vehicles in real traffic. This sample is representative of the Algerian light vehicles in terms of fuel quality (gasoline, diesel and liquefied petroleum gas) and the technology quality (injection system and emission control). The experimental measurement methodology of unit emission of vehicles in real traffic situation is based on the use of the mini-Constant Volume Sampler for gas sampling and a set of gas analyzers for CO2, CO, NOx and THC, with an instrumentation to measure kinematics, gas temperature and pressure. The apparatus is also equipped with data logging instrument and data transfer. The results were compared with the database of the European light vehicles (Artemis). It was shown that the technological injection liquefied petroleum gas (LPG) has significant impact on air pollutants emission. Therefore, with the exception of nitrogen oxide compounds, uncatalyzed LPG vehicles are more effective in reducing emissions unit of air pollutants compared to uncatalyzed gasoline vehicles. LPG performance seems to be lower under real driving conditions than expected on chassis dynamometer. On the other hand, the results show that uncatalyzed gasoline vehicles emit high levels of carbon monoxide, and nitrogen oxides. Overall, and in the absence of standards in Algeria, unit emissions are much higher than Euro 3. The enforcement of pollutant emission standard in developing countries is an important step towards introducing cleaner technology and reducing vehicular emissions.

Keywords: on-board measurements of unit emissions of CO, HC, NOx and CO2, light vehicles, mini-CVS, LPG-fuel, artemis, Algeria

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Authors: Tania Vazquez, Aida Huerta

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Way to get our food has changed over the time, and it is a daily necessity. Nowadays we found a lot of problems involved with the economy, environment, and society, which affect the agrifood system. Some problems as construction of big cities and growing population have been increasing demand food directly. Due to the countryside are far away from the city, another alternative systems have come from, such as Urban Agriculture (UA). UA system offers food production into the cities, products with characteristics as quality, healthy and good prices, close to the customers, recycling culture and the promote environmental education. Last years in Mexico City urban gardens have taken strongly in various politic delegations. There are establishment’s public and private initiatives. Moreover, these places have had different issues like low income, many activities, few workers, low production, lack of training and advice, devaluation of your work and low sales, all these shortcomings generate the devaluation of their work. The aim of this paper is to evaluate a business plan in Mexico City´s urban gardens that contribute to ensuring economic, environmental and social sustainability; to adjust business plan for this places so that they reach viability over time. As a part of soft systems methodology developed of Peter Checkland, we interviewed owners of urban gardens and we found that recurring problem was lack planning manager activities and a master plan about their business. We evaluate the business plan based on “Ten principles in sustainable food value chain development” proposed for Food and Agriculture Organization of the United Nations (FAO). With this study was possible measure, understand and improve performance of business plan in the three pillars of the sustainability in addition to this it allowed us to fit in with the needs of urban gardens.

Keywords: business plan, Mexico City, urban agriculture, urban gardens

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Authors: Ahmed F. Azmy, Amal E. Saafan, Tamer M. Essam, Magdy A. Amin, Shaban H. Ahmed

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Bacterial strains capable of degradation of malathion from the domestic sewage were isolated by an enrichment culture technique. Three bacterial strains were screened and identified as Acinetobacter baumannii (AFA), Pseudomonas aeruginosae (PS1),andPseudomonas mendocina (PS2) based on morphological, biochemical identification and 16S rRNA sequence analysis. Acinetobacter baumannii AFA was the most efficient malathion degrading bacterium, so used for further biodegradation study. AFA was able to grow in mineral salt medium (MSM) supplemented with malathion (100 mg/l) as a sole carbon source, and within 14 days, 84% of the initial dose was degraded by the isolate measured by high performance liquid chromatography. Strain AFA could also degrade other organophosphorus compounds including diazenon, chlorpyrifos and fenitrothion. The effect of different culture conditions on the degradation of malathion like inoculum density, other carbon or nitrogen sources, temperature and shaking were examined. Degradation of malathion and bacterial cell growth were accelerated when culture media were supplemented with yeast extract, glucose and citrate. The optimum conditions for malathion degradation by strain AFA were; an inoculum density of 1.5x 1012CFU/ml at 30°C with shaking. A specific polymerase chain reaction primers were designed manually using multiple sequence alignment of the corresponding carboxylesterase enzymes of Acinetobacter species. Sequencing result of amplified PCR product and phylogenetic analysis showed low degree of homology with the other carboxylesterase enzymes of Acinetobacter strains, so we suggested that this enzyme is a novel esterase enzyme. Isolated bacterial strains may have potential role for use in bioremediation of malathion contaminated.

Keywords: Acinetobacter baumannii, biodegradation, malathion, organophosphate pesticides

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Authors: Arif Sikander, Imran Saeed

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The behavioral pattern and performance of airline pilots are influenced by the level of stress, their ethical decision-making ability and above all their leadership style as part of the Crew Management process. Cultural differences of pilots, especially while working in ex-country airlines, could influence the stress perception. Culture also influences ethical decision making. Leadership style is also a variable dimension, and pilots need to adapt to the cultural settings while flying with the local pilots as part of their team. Studies have found that age, education, gender, and management experience are statistically significant factors in ethical maturity. However, in the decades to come, more studies are required to validate the results over and over again; thereby, providing support for the validity of the Moral Development Theory. Leadership style plays a vital role in ethical decision making. This study is grounded in the Moral Development theory and seeks to analyze the styles of leadership of airline pilots related to ethical decision making and also the influence of the culture on their stress perception. The sample for the study included commercial pilots from a National Airline. It is expected that these results should provide useful input to the literature in the context of developing appropriate Talent Management strategies. The authors intend to extend this study (carried out in one country) to major national carriers (many countries) to be able to develop a ultimate framework on Talent Management which should serve as a benchmark for any international airline as most of them (e.g., Emirates, Etihad, Cathay Pacific, China Southern, etc.) are dependent on the supply of this scarce resource from outside countries.

Keywords: ethics, leadership, pilot, stress

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Authors: Norah Al Hokbany, Ibrahim Al Jammaz, Basem Al Otaibi, Yousif Al Malki, Subhani M. Okarvi

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Objective: The folate receptor is over-expressed in a wide variety of human tumors. Conjugates of folate have been shown to be selectively taken up by tumor cells via the folate receptor. In an attempt to develop new folate radiotracers with favorable biochemical properties for detecting folate receptor-positive cancers. Methods: we synthesized ⁶⁴Cu-NOTA- and ⁶⁴Cu-NOTAM-folate conjugates using a straightforward and simple one-step reaction. Radiochemical yields were greater than 95% (decay-corrected) with a total synthesis time of less than 20 min. Results: Radiochemical purities were always greater than 98% without high-performance liquid chromatography (HPLC) purification. These synthetic approaches hold considerable promise as a rapid and simple method for ⁶⁴Cu-folate conjugate preparation with high radiochemical yield in a short synthesis time. In vitro tests on the KB cell line showed that significant amounts of the radio conjugates were associated with cell fractions. Bio-distribution studies in nude mice bearing human KB xenografts demonstrated a significant tumor uptake and favorable bio-distribution profile for ⁶⁴Cu-NOTA- and ⁶⁴Cu-NOTAM-folate conjugate. The uptake in the tumors was blocked by the excess injection of folic acid, suggesting a receptor-mediated process. Conclusion: These results demonstrate that the ⁶⁴Cu-NOTAM-folate conjugate may be useful as a molecular probe for the detection and staging of folate receptor-positive cancers, such as ovarian cancer and their metastasis, as well as monitoring tumor response to treatment.

Keywords: folate, receptor, tumor imaging, ⁶⁴Cu-NOTA-folate, PET

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Authors: Professor Jo Angouri, Polina Mesinioti, Chris Turner

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In order for a group of ad-hoc professional to perform as a team, a shared understanding of the problem at hand and an agreed action plan are necessary components. This is particularly significant in complex, time sensitive professional settings such as in trauma emergencies. In this context, team briefings prior to the patient arrival (pre-briefings) constitute a critical event for the performance of the team; they provide the necessary space for co-constructing a shared understanding of the situation through summarising information available to the team: yet the act of summarising is widely assumed in medical practice but not systematically researched. In the vast teamwork literature, terms such as ‘shared mental model’, ‘mental space’ and ‘cognate labelling’ are used extensively, and loosely, to denote the outcome of the summarising process, but how exactly this is done interactionally remains under researched. This paper reports on the forms and functions of pre-briefings in a major trauma centre in the UK. Taking an interactional approach, we draw on 30 simulated and real-life trauma emergencies (15 from each dataset) and zoom in on the use of pre-briefings, which we consider focal points in the management of trauma emergencies. We show how ad hoc teams negotiate sharedness of future orientation through summarising, synthesising information, and establishing common understanding of the situation. We illustrate the role, characteristics, and structure of pre-briefing sequences that have been evaluated as ‘efficient’ in our data and the impact (in)effective pre-briefings have on teamwork. Our work shows that the key roles in the event own the act of summarising and we problematise the implications for leadership in trauma emergencies. We close the paper with a model for pre-briefing and provide recommendations for clinical practice, arguing that effective pre-briefing practice is teachable.

Keywords: summarising, medical emergencies, interaction analysis, shared/mental models

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Authors: R. Saravanakumar, A. Siva, R. Banupriya, K. Balasubramanian

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Slurry infiltrated fibrous concrete (SIFCON) is one of the recently developed construction material that can be considered as a special type of high performance fibre reinforced concrete (HPFRC) with higher fibre content. Fibre reinforced concrete is essentially a composite material in which fibres out of waste having higher modulus of elasticity. SIFCON is a special type of high fibrous concrete and it is having a high cementious content and sand. The matrix usually consists of cement-sand slurry or fluent mortar. The construction industry is in need of finding cost effective materials for increasing the strength of concrete structures hence an endeavour has been made in the present investigations to study the influence of addition of waste material like Lathe waste from workshop at different dosages to the total weight of concrete. The waste of steel scrap material which is available from the lathe is used as a steel fibre for innovative construction industry. To get sustainable and environmental benefits, lathe scrap as recycled fibres with concrete are likely to be used. An experimental program was carried out to investigate the flexural behavior of Slurry infiltrated fibrous concrete (SIFCON) in which the fibres having an aspect ratio of 100 is used. The investigations were done using M25 mix and tests were carried out as per recommended procedures by appropriate codes. SIFCON specimens with 8%, 10% and 12% volume of fraction fibres are used in this study. Test results were presented in comparison of SIFCON with and without conventional steel reinforcement. The load carrying capacity of SIFCON specimen is higher than conventional concrete and it also reduced crack width. In the SIFCON specimen less number of cracks as compared with conventional concrete.

Keywords: SIFCON, lathe waste, RCC, fibre volume, flexural behaviour

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Authors: Chinwendu R. Nnabalu, Gioia Falcone, Imma Bortone

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Petroleum refining is a chemical process in which the raw material (crude oil) is converted to finished commercial products for end users. The fluid catalytic cracking (FCC) unit is a key asset in refineries, requiring optimised processes in the context of engineering design. Following the first stage of separation of crude oil in a distillation tower, an additional 40 per cent quantity is attainable in the gasoline pool with further conversion of the downgraded product of crude oil (residue from the distillation tower) using a catalyst in the FCC process. Effective removal of sulphur oxides, nitrogen oxides, carbon and heavy metals from FCC gasoline requires greater separation efficiency and involves an enormous environmental significance. The FCC unit is primarily a reactor and regeneration system which employs cyclone systems for separation.  Catalyst losses in FCC cyclones lead to high particulate matter emission on the regenerator side and fines carryover into the product on the reactor side. This paper aims at demonstrating the importance of FCC unit design criteria in terms of technical performance and compliance with environmental legislation. A systematic review of state-of-the-art FCC technology was carried out, identifying its key technical challenges and sources of emissions.  Case studies of petroleum refineries in Nigeria were assessed against selected global case studies. The review highlights the need for further modelling investigations to help improve FCC design to more effectively meet product specification requirements while complying with stricter environmental legislation.

Keywords: design, emission, fluid catalytic cracking, petroleum refineries

Procedia PDF Downloads 138

Authors: Carlos Gonzales, Zaida Quiroz, Marcos Prates

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Several spatial variables collected at the same location that share a common spatial distribution can be modeled simultaneously through a multivariate geostatistical model that takes into account the correlation between these variables and the spatial autocorrelation. The main goal of this model is to perform spatial prediction of these variables in the region of study. Here we focus on a geostatistical multivariate formulation that relies on sharing common spatial random effect terms. In particular, the first response variable can be modeled by a mean that incorporates a shared random spatial effect, while the other response variables depend on this shared spatial term, in addition to specific random spatial effects. Each spatial random effect is defined through a Gaussian process with a valid covariance function, but in order to improve the computational efficiency when the data are large, each Gaussian process is approximated to a Gaussian random Markov field (GRMF), specifically to the block nearest neighbor Gaussian process (Block-NNGP). This approach involves dividing the spatial domain into several dependent blocks under certain constraints, where the cross blocks allow capturing the spatial dependence on a large scale, while each individual block captures the spatial dependence on a smaller scale. The multivariate geostatistical model belongs to the class of Latent Gaussian Models; thus, to achieve fast Bayesian inference, it is used the integrated nested Laplace approximation (INLA) method. The good performance of the proposed model is shown through simulations and applications for massive data.

Keywords: Block-NNGP, geostatistics, gaussian process, GRMF, INLA, multivariate models.

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Authors: Hayriye Anıl, Görkem Kar

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In addition to being rich in renewable energy resources, Turkey is one of the countries that promise potential in geothermal energy production with its high installed power, cheapness, and sustainability. Increasing imbalance penalties become an economic burden for organizations since geothermal generation plants cannot maintain the balance of supply and demand due to the inadequacy of the production forecasts given in the day-ahead market. A better production forecast reduces the imbalance penalties of market participants and provides a better imbalance in the day ahead market. In this study, using machine learning, deep learning, and, time series methods, the total generation of the power plants belonging to Zorlu Natural Electricity Generation, which has a high installed capacity in terms of geothermal, was estimated for the first one and two weeks of March, then the imbalance penalties were calculated with these estimates and compared with the real values. These modeling operations were carried out on two datasets, the basic dataset and the dataset created by extracting new features from this dataset with the feature engineering method. According to the results, Support Vector Regression from traditional machine learning models outperformed other models and exhibited the best performance. In addition, the estimation results in the feature engineering dataset showed lower error rates than the basic dataset. It has been concluded that the estimated imbalance penalty calculated for the selected organization is lower than the actual imbalance penalty, optimum and profitable accounts.

Keywords: machine learning, deep learning, time series models, feature engineering, geothermal energy production forecasting

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Authors: Wambugu Naftaly, Ruisheng Wang, Zhijun Wang

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Models based on convolutional neural networks (CNNs), in conjunction with Transformer, have excelled in semantic segmentation, a fundamental task for intelligent Earth observation using remote sensing (RS) imagery. Nonetheless, tokenization in the Transformer model undermines object structures and neglects inner-patch local information, whereas CNNs are unable to simulate global semantics due to limitations inherent in their convolutional local properties. The integration of the two methodologies facilitates effective global-local feature aggregation and interactions, potentially enhancing segmentation results. Inspired by the merits of CNNs and Transformers, we introduce a layer-level feature aggregation network (LLFA-Net) to address semantic segmentation of fine-resolution remote sensing (FRRS) images for land cover classification. The simple yet efficient system employs a transposed unit that hierarchically utilizes dense high-level semantics and sufficient spatial information from various encoder layers through a layer-level feature aggregation module (LLFAM) and models global contexts using structured Transformer blocks. Furthermore, the decoder aggregates resultant features to generate rich semantic representation. Extensive experiments on two public land cover datasets demonstrate that our proposed framework exhibits competitive performance relative to the most recent frameworks in semantic segmentation.

Keywords: land cover mapping, semantic segmentation, remote sensing, vision transformer networks, deep learning

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Authors: P. Wongmatar, C. Hansapinyo, C. Buachart

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Failure of typical seismic frames has been found by plastic hinge occurring on beams section near column faces. Past researches shown that the seismic capacity of the frames can be enhanced if the plastic hinges of the beams are shifted away from the column faces. This paper presents detailing of reinforcements in the interior beam–column connections aiming to relocate the plastic hinge of reinforced concrete and precast concrete frames. Four specimens were tested under quasi-static cyclic load including two monolithic specimens and two precast specimens. For one monolithic specimen, typical seismic reinforcement was provided and considered as a reference specimen named M1. The other reinforced concrete frame M2 contained additional intermediate steel in the connection area compared with the specimen M1. For the precast specimens, embedded T-section steels in joint were provided, with and without diagonal bars in the connection area for specimen P1 and P2, respectively. The test results indicated the ductile failure with beam flexural failure in monolithic specimen M1 and the intermediate steel increased strength and improved joint performance of specimen M2. For the precast specimens, cracks generated at the end of the steel inserts. However, slipping of reinforcing steel lapped in top of the beams was seen before yielding of the main bars leading to the brittle failure. The diagonal bars in precast specimens P2 improved the connection stiffness and the energy dissipation capacity.

Keywords: relocation, plastic hinge, intermediate bar, T-section steel, precast concrete frame

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Authors: Mukhtari Hussaini Muhammad, Abba Adamu

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The paper will examine the approaches and solutions that will be offered by Senior Secondary School II Students (Demonstration Secondary School, Azare Bauchi State Northern Nigeria – Hausa/ Fulani predominant area) toward solving exercises related to the circle theorem. The angle that an arc of a circle subtends at the center is twice that which it subtends at any point on the remaining part of the circumference. The Students will be divided in to 2 groups by given them numbers 1, 2; 1, 2; 1, 2, then all 1s formed group I and all 2s formed group II. Group I will be considered as control group in which the traditional method will be applied during instructions. Thus, the researcher will revise the concept of circle, state the theorem, prove the theorem and then solve examples. Group II, experimental group in which the concept of circle will be revised to the students and then the students will be asked to draw different circles, mark arcs, draw angle at the center, angle at the circumference then measure the angles constructed. The students will be asked to explain what they can infer/deduce from the angles measured and lastly, examples will be solved. During the next contact day, both groups will be subjected to solving exercises in the classroom related to the theorem. The angle that an arc of a circle subtends at the center is twice that which it subtends at any point on the remaining part of circumference. The solution to the exercises will be marked, the scores compared/analysed using relevant statistical tool. It is expected that group II will perform better because of the method/ technique followed during instructions is more learner-centered. By exploiting the talents of the individual learners through listening to the views and asking them how they arrived at a solution will really improve learning and understanding.

Keywords: circle theorem, control group, experimental group, traditional method

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Authors: Taher M. Abou-deif, Esmail M. El-Bialy, Essam E. Khalil

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The paper is devoted to numerically investigating the influence of the air supply outlets geometry on human comfort inside living looms. A computational fluid dynamics model is developed to examine the air flow characteristics of a room with different supply air diffusers. The work focuses on air flow patterns, thermal behavior in the room with few number of occupants. As an input to the full-scale 3-D room model, a 2-D air supply diffuser model that supplies direction and magnitude of air flow into the room is developed. Air distribution effect on thermal comfort parameters was investigated depending on changing the air supply diffusers type, angles and velocity. Air supply diffusers locations and numbers were also investigated. The pre-processor Gambit is used to create the geometric model with parametric features. Commercially available simulation software “Fluent 6.3” is incorporated to solve the differential equations governing the conservation of mass, three momentum and energy in the processing of air flow distribution. Turbulence effects of the flow are represented by the well-developed two equation turbulence model. In this work, the so-called standard k-ε turbulence model, one of the most widespread turbulence models for industrial applications, was utilized. Basic parameters included in this work are air dry bulb temperature, air velocity, relative humidity and turbulence parameters are used for numerical predictions of indoor air distribution and thermal comfort. The thermal comfort predictions through this work were based on ADPI (Air Diffusion Performance Index),the PMV (Predicted Mean Vote) model and the PPD (Percentage People Dissatisfied) model, the PMV and PPD were estimated using Fanger’s model.

Keywords: thermal comfort, Fanger's model, ADPI, energy effeciency

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Authors: Maryam Hamlehdar, Guillermo A. Narsilio

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To enhance the feasibility of utilising geothermal hot sedimentary aquifers (HSAs) for clean hydrogen production, one approach is the implementation of solar-integrated geothermal energy systems. This detailed modelling study conducts a thermo-economic assessment of an advanced Organic Rankine Cycle (ORC)-based hydrogen production system that uses low-temperature geothermal reservoirs, with a specific focus on hot sedimentary aquifers (HSAs) over a 30-year period. In the proposed hybrid system, solar-thermal energy is used to raise the water temperature extracted from the geothermal production well. This temperature increase leads to a higher steam output, powering the turbine and subsequently enhancing the electricity output for running the electrolyser. Thermodynamic modeling of a parabolic trough solar (PTS) collector is developed and integrated with modeling for a geothermal-based configuration. This configuration includes a closed regenerator cycle (CRC), proton exchange membrane (PEM) electrolyser, and thermoelectric generator (TEG). Following this, the study investigates the impact of solar energy use on the temperature enhancement of the geothermal reservoir. It assesses the resulting consequences on the lifecycle performance of the hydrogen production system in comparison with a standalone geothermal system. The results indicate that, with the appropriate solar collector area, a combined solar-geothermal hydrogen production system outperforms a standalone geothermal system in both cost and rate of production. These findings underscore a solar-assisted geothermal hybrid system holds the potential to generate lower-cost hydrogen with enhanced efficiency, thereby boosting the appeal of numerous low to medium-temperature geothermal sources for hydrogen production.

Keywords: clean hydrogen production, integrated solar-geothermal, low-temperature geothermal energy, numerical modelling

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Authors: Chiara De Amicis, Sonia Falconieri, Mesut Tastan

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In this study, we analyze the language employed by Chief Executive Officers (CEOs) and Chief Financial Officers (CFOs) during earnings conference calls from a gender perspective. We find evidences that conference calls held by female CEOs and/or CFOs exhibit a higher level of optimism compared to conference calls held by male CEOs and/or CFOs. Moreover, female managers tend to present and discuss firm performances with less vagueness as compared to their male colleagues. We then observe the market reaction around each earnings conference call: while manager optimism is perceived as a good signal by investors, manager vagueness significantly dampens the market reaction around the call. Whether the gender of the CEO and/or the CFO delivering the conference call affects investors’ perceptions about the firm performance is still an open question. Some evidences show that the language employed by female managers conveys more valuable information for market participants as compared to the language employed by their male counterparts. This study contributes to a growing literature in finance and accounting that uses textual analysis to assess the informativeness of corporate disclosure. To our knowledge, this is the first paper that aims at answering the question whether the gender of firm’s top managers does matter when it comes to assess the informativeness of corporate spoken communication. We believe that our results will be of relevance for future research in the field. Moreover, our evidence may be used in support of the debate if a larger participation by women in the management of companies should be encouraged or not.

Keywords: conference calls, even study, gender, market reaction, textual analysis

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Authors: Neil Jolly, Louisa Beukes, Santiago Benito-SaEz

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Kei-apple is a tree found on the African continent. Limited information exists on the effect of alcoholic and acetous fermentation on the phytochemicals. The fruit has increased L-malic, ascorbic, and phenolic acids. Juice was co-inoculated with Schizosaccharomyces pombe and Saccharomyces cerevisiae to induce alcoholic fermentation and acetous fermentation using acetic acid bacteria. Saccharomyces cerevisiae+S. pombe wines and vinegars had highest pH. Total acidity, soluble solids and L-malic acid decreased during alcoholic and acetous fermentation with highest in S. cerevisiae wines and vinegars. Volatile acidity was highest in S. pombe vinegars but not different from S. cerevisiae and S. cerevisiae+S. pombe. Gallic acid was highest in S. pombe wines and vinegars. Syringic acid was highest in S. cerevisiae wines and vinegars. S. cerevisiae+S. pombe wines were highest in caffeic, p-coumaric and protocatechuic acids. Schizosaccharomyces pombe vinegars were highest in caffeic and p-coumaric acids. Ferulic and sinapic acids were highest in S. pombe and S. cerevisiae wines, respectively. Chlorogenic acid was most abundant in both wines and vinegars. Saccharomyces cerevisiae+S. pombe and S. cerevisiae had a positive effect on most phenolic acids. Saccharomyces cerevisiae +acetic acid bacteria had an increased effect on syringic and chlorogenic acids. Schizosaccharomyces pombe+acetic acid bacteria resulted in an increase in gallic, caffeic and p-coumaric acids. Acetic acid bacteria had minimal performance with respect to volatile acidity production in comparison to commercial vinegars. Acetic acid bacteria selection should therefore be reconsidered and the decrease of certain phenolic acids during acetous fermentation needs to be investigated.

Keywords: acetic acid bacteria, liquid chromatography, phenolics, saccharomyces cerevisiae, schizosaccharomyces pombe

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Authors: Maydariana Ayuningtyas, Bambang Riyanto, Akhiruddin Maddu

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Industrial waste of crustacean shells, such as shrimp and crab, has been considered as one of the major issues contributing to environmental pollution. The waste processing mechanisms to form new, practical substances with added value have been developed. Chitosan, a derived matter from chitin, which is obtained from crab and shrimp shells, performs prodigiously in broad range applications. A chitosan composite-based diaphragm is a new inspiration in fiber optic acoustic sensor advancement. Elastic modulus, dynamic response, and sensitivity to acoustic wave of chitosan-based composite film contribute great potentials of organic-based sound-detecting material. The objective of this research was to develop chitosan diaphragm application in fiber optic microphone system. The formulation was conducted by blending 5% polyvinyl alcohol (PVA) solution with dissolved chitosan at 0%, 1% and 2% in 1:1 ratio, respectively. Composite diaphragms were characterized for the morphological and mechanical properties to predict the desired acoustic sensor sensitivity. The composite with 2% chitosan indicated optimum performance with 242.55 µm thickness, 67.9% relative humidity, and 29-76% light transmittance. The Young’s modulus of 2%-chitosan composite material was 4.89×104 N/m2, which generated the voltage amplitude of 0.013V and performed sensitivity of 3.28 mV/Pa at 1 kHz. Based on the results above, chitosan from crustacean shell waste can be considered as a viable alternative material for fiber optic acoustic sensor sensing pad development. Further, the research in chitosan utilisation is proposed as novel optical microphone development in anthropogenic noise controlling effort for environmental and biodiversity conservation.

Keywords: acoustic sensor, chitosan, composite, crab shell, diaphragm, waste utilisation

Procedia PDF Downloads 260

Authors: R. Hosny, Mahmoud F. Mubarak, Heba M. Salem, Asmaa A. Abdelrahman

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Oilfield scaling is a major problem in the oil and gas industry. Scale issues cost the industry millions of dollars in damage and lost production every year. One of the main causes of global production decline is scale. In this study, solid scale inhibitors based on silver tungstate loaded KIT-6 were synthesized and evaluated in both static and scale inhibition modeling. The silver tungstate loaded KIT-6 catalysts were synthesized via a simple impregnated method using 3D mesoporous KIT-6 as support. The synthesized materials were characterized using wide and low XRD, N2 adsorption–desorption analysis, TGA analysis, and FTIR, SEM, and XPS analysis. The scale inhibition efficiency of the synthesized materials was evaluated using a static scale inhibition test. The results of this study demonstrate the potential application of silver tungstate-loaded KIT-6 solid scale inhibitors for the oil and gas industry. The results of this study will contribute to the development of new and innovative solid scale inhibitors based on silver tungstate-loaded KIT-6. The inhibition efficiency of the scale inhibitor increases, and calcite scale inhibitor decreases with increasing pH (2 to8), it proposes that the scale inhibitor was more effective under alkaline conditions. An inhibition efficiency of 99% on calcium carbonate can be achieved at the optimal dosage of 7.5 ppm at 55oC, indicating that the scale inhibitor exhibits a relatively good inhibition performance on calcium carbonate. The use of these materials can potentially lead to more efficient and cost-effective solutions for scaling inhibition in various industrial processes.

Keywords: produced water treatment, solid scale inhibitors, calcite, silver tungestate, 3 D mesoporous KIT-6, oilfield scales, adsorption

Procedia PDF Downloads 145

Authors: Kamal KC, Zhendong Yin, Dasen Li, Zhilu Wu

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Intra-plant disease classification based on leaf images is a challenging computer vision task due to similarities in texture, color, and shape of leaves with a slight variation of leaf spot; and external environmental changes such as lighting and background noises. Deep convolutional neural network (DCNN) has proven to be an effective tool for binary classification. In this paper, two methods for binary classification of diseased plant leaves using DCNN are presented; model created from scratch and transfer learning. Our main contribution is a thorough evaluation of 4 networks created from scratch and transfer learning of 5 pre-trained models. Training and testing of these models were performed on a plant leaf images dataset belonging to 16 distinct classes, containing a total of 22,265 images from 8 different plants, consisting of a pair of healthy and diseased leaves. We introduce a deep CNN model, Optimized MobileNet. This model with depthwise separable CNN as a building block attained an average test accuracy of 99.77%. We also present a fine-tuning method by introducing the concept of a convolutional block, which is a collection of different deep neural layers. Fine-tuned models proved to be efficient in terms of accuracy and computational cost. Fine-tuned MobileNet achieved an average test accuracy of 99.89% on 8 pairs of [healthy, diseased] leaf ImageSet.

Keywords: deep convolution neural network, depthwise separable convolution, fine-grained classification, MobileNet, plant disease, transfer learning

Procedia PDF Downloads 188

Authors: Sijing Xiong, Ran Su, Lit-Hsin Loo, Daniele Zink

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The kidney is a major target for toxic effects of drugs, industrial and environmental chemicals and other compounds. Typically, nephrotoxicity is detected late during drug development, and regulatory animal models could not solve this problem. Validated or accepted in silico or in vitro methods for the prediction of nephrotoxicity are not available. We have established the first and currently only pre-validated in vitro models for the accurate prediction of nephrotoxicity in humans and the first predictive platforms based on renal cells derived from human pluripotent stem cells. In order to further improve the efficiency of our predictive models, we recently developed a high content screening (HCS) platform. This platform employed automated imaging in combination with automated quantitative phenotypic profiling and machine learning methods. 129 image-based phenotypic features were analyzed with respect to their predictive performance in combination with 44 compounds with different chemical structures that included drugs, environmental and industrial chemicals and herbal and fungal compounds. The nephrotoxicity of these compounds in humans is well characterized. A combination of chromatin and cytoskeletal features resulted in high predictivity with respect to nephrotoxicity in humans. Test balanced accuracies of 82% or 89% were obtained with human primary or immortalized renal proximal tubular cells, respectively. Furthermore, our results revealed that a DNA damage response is commonly induced by different PTC-toxicants with diverse chemical structures and injury mechanisms. Together, the results show that the automated HCS platform allows efficient and accurate nephrotoxicity prediction for compounds with diverse chemical structures.

Keywords: high content screening, in vitro models, nephrotoxicity, toxicity prediction

Procedia PDF Downloads 314

Authors: Ranjeet Sable, Mahotsavi Patil, Aadesh Nimbalkar, Prajakta Palaskar, Ritu Sagar

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The exact amount of water used by various crops in different climatic conditions is necessary to step for design, planning, and management of irrigation schemes, water resources, scheduling of irrigation systems. Evaporation and transpiration are combinable called as evapotranspiration. Water loss from trees during photosynthesis is called as transpiration and when water gets converted into gaseous state is called evaporation. For calculation of correct evapotranspiration, we have to choose the method in such way that is should be suitable and require minimum climatic data also it should be applicable for wide range of climatic conditions. In hydrology, there are multiple correlations and regression is generally used to develop relationships between three or more hydrological variables by knowing the dependence between them. This research work includes the study of various methods for calculation of evapotranspiration and selects reasonable and suitable one Pune region (Maharashtra state). As field methods are very costly, time-consuming and not give appropriate results if the suitable climate is not maintained. Observation recorded at Pune metrological stations are used to calculate evapotranspiration with the help of Radiation Method (RAD), Modified Penman Method (MPM), Thornthwaite Method (THW), Blaney-Criddle (BCL), Christiansen Equation (CNM), Hargreaves Method (HGM), from which Hargreaves and Thornthwaite are temperature based methods. Performance of all these methods are compared with Modified Penman method and method which showing less variation with standard Modified Penman method (MPM) is selected as the suitable one. Evapotranspiration values are estimated on a monthly basis. Comparative analysis in this research used for selection for raw data-dependent methods in case of missing data.

Keywords: Blaney-Criddle, Christiansen equation evapotranspiration, Hargreaves method, precipitations, Penman method, water use efficiency

Procedia PDF Downloads 271

Authors: A. Moawad, K. C. Yao, A. Mansour, R. Gautier

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The detecting of an occupied frequency band is a major issue in cognitive radio systems. The detection process becomes difficult if the signal occupying the band of interest has faded amplitude due to multipath effects. These effects make it hard for an occupying user to be detected. This work mitigates the missed-detection problem in the context of cognitive radio in frequency-selective fading channel by proposing blind channel estimation method that is based on scattering transform. By initially applying conventional energy detection, the missed-detection probability is evaluated, and if it is greater than or equal to 50%, channel estimation is applied on the received signal followed by channel equalization to reduce the channel effects. In the proposed channel estimator, we modify the Morlet wavelet by using its first derivative for better frequency resolution. A mathematical description of the modified function and its frequency resolution is formulated in this work. The improved frequency resolution is required to follow the spectral variation of the channel. The channel estimation error is evaluated in the mean-square sense for different channel settings, and energy detection is applied to the equalized received signal. The simulation results show improvement in reducing the missed-detection probability as compared to the detection based on principal component analysis. This improvement is achieved at the expense of increased estimator complexity, which depends on the number of wavelet filters as related to the channel taps. Also, the detection performance shows an improvement in detection probability for low signal-to-noise scenarios over principal component analysis- based energy detection.

Keywords: channel estimation, cognitive radio, scattering transform, spectrum sensing

Procedia PDF Downloads 198

Authors: Francesco Ceresia

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Workplace aggression is broadly recognized as a main work-related risk for healthcare organizations the world over. Scholars underlined that nonfatal workplace aggressions can be also produced by Type II workplace aggression, that occur when the aggressor has a legitimate relationship with the organization and commits an act of hostility while being served or cared for by members of the organization. Several reviews and meta-analysis highlighted the main antecedents and consequences of Type II verbal and physical workplace aggression in the healthcare sector, also focusing on its economic and psychosocial costs. However, some scholars emphasized the need for a systemic and multi-factorial approach to deeply understand and effectively respond to such kind of aggression. The main aim of the study is to propose a qualitative model of Type II workplace aggression in a health care organization in accordance with the system thinking and multi-factorial perspective. A case study research approach, conducted in an Italian non-hospital healthcare organization, is presented. Two main data collection methods have been adopted: individual and group interviews with a sample (N = 24) of physicians, nurses and clericals. A causal loop diagram (CLD) that describes the main causal relationships among the key-variables of the proposed model has been outlined. The main feedback loops and the causal link polarities have been also defined to fully describe the structure underlining the Type II workplace aggression phenomenon. The proposed qualitative model shows how the Type II workplace aggression is related with burnout, work performance, job satisfaction, turnover intentions, work motivation and emotional dissonance. Finally, strategies and policies to reduce the strength of workplace aggression’s drivers are suggested.

Keywords: healthcare, system thinking, work motivation, workplace aggression

Procedia PDF Downloads 306

Authors: Usama Abdulwahab, Mohammed Wahab

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This paper presents the application of uncapacitated facility location problems (UFLP) and 1-median problems to support decision making in blood supply chain networks. A plethora of factors make blood supply-chain networks a complex, yet vital problem for the regional blood bank. These factors are rapidly increasing demand; criticality of the product; strict storage and handling requirements; and the vastness of the theater of operations. As in the UFLP, facilities can be opened at any of $m$ predefined locations with given fixed costs. Clients have to be allocated to the open facilities. In classical location models, the allocation cost is the distance between a client and an open facility. In this model, the costs are the allocation cost, transportation costs, and inventory costs. In order to address this problem the median algorithm is used to analyze inventory, evaluate supply chain status, monitor performance metrics at different levels of granularity, and detect potential problems and opportunities for improvement. The Euclidean distance data for some Ontario cities (demand nodes) are used to test the developed algorithm. Sitation software, lagrangian relaxation algorithm, and branch and bound heuristics are used to solve this model. Computational experiments confirm the efficiency of the proposed approach. Compared to the existing modeling and solution methods, the median algorithm approach not only provides a more general modeling framework but also leads to efficient solution times in general.

Keywords: approximate dynamic programming, facility location, perishable product, inventory model, blood platelet, P-median problem

Procedia PDF Downloads 508

Authors: Lapatrada Numkham, Saowaluk Khakhong, Jeeraporn Kummabutr

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Non-communicable diseases (NCDs) are the leading cause of death in worldwide. Thailand also concerns and focuses on reduction a new case of these diseases. Community Health Volunteers (CHV) is important health personnel in primary health care and performs as a health leader in the community. If the health of CHV changes, it would impact on the performance to promote health of families and community. This cross-sectional study aimed to 1) describe the health status of community health volunteers and 2) examine the factors associated with health status among community health volunteers. The sample included 360 community health volunteers in a province in central Thailand during September-December 2014. Data were collected using questionnaires on health information, knowledge of health behaviors, and health behaviors. Body weight, height, waist circumference (WC), blood pressure (BP), and blood glucose (BS) (fingertip) were assessed. Data were analyzed using descriptive statistics and chi-square test. There were three hundred and sixty participants with 82.5% being women. The mean age was 54 + 8.9 years. Forty-seven percent of the participants had co-morbidities. Hypertension was the most common co-morbidity (26.7%). The results revealed that the health status of the volunteers included: no underlying disease, having risk of hypertension (HT) & diabetes mellitus (DM), and having HT&DM at 38.3%, 30.0%, and 31.7% respectively. The chi-square test revealed that the factors associated with health status among the volunteers were gender, age, WC and body mass index (BMI). The results suggested that community health nurses should; 1) implement interventions to decrease waist circumference and lose weight through education programs, especially females; 2) monitor people that have a risk of HT&DM and that have HT&DM by meeting and recording BP level, BS level, WC and BMI; and 3) collaborate with a district public health officer to initiate a campaign to raise awareness of the risks of chronic diseases among community health volunteers.

Keywords: community health volunteers, health status, risk of non-communicable disease, Thailand

Procedia PDF Downloads 361